Senior Principal Architect, Applied AI Enterprise

** Career Area:
** Technology, Digital and Data
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* Job Description:

**** Your Work Shapes the World at Caterpillar Inc.
** When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other.  We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live.

Together, we are building a better world, so we can all enjoy living in it.
*
* Job Summary:

** Join the AI Acceleration team and help shape how Caterpillar builds and deploys AI-powered solutions across the enterprise. As a Senior AI Architect/Engineer, you'll serve as a technical leader and trusted advisor on the AI solution design - with a focus on agentic systems that can reason, plan and take action. You'll partner with IT, business functions and product teams to ensure we're building AI solutions that are architecturally sound, scalable and aligned with where the industry is heading.
This is a high-visibility role with direct impact on Caterpillar's AI strategy and the opportunity to get hands-on with emerging technologies
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* What You Will Do:

*** Developing detailed architecture deliverables to solve business problems through agentic AI systems and patterns.
* Designing an AI application's technical infrastructure, including orchestration layers, tool integrations, data retrieval patterns, and testing approaches.
* Leading the evaluation and deployment of emerging AI technologies and frameworks to enhance Caterpillar's agentic capabilities.
* Participating in translating business requirements into AI solution designs and collaborating with cross-functional teams to deliver results.
** What

You Will Have:

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* ** Effective Communications:
** Expert understanding of effective communication concepts, tools and techniques; ability to effectively transmit, receive, and accurately interpret ideas, information, and needs through the application of appropriate communication behaviors.
* ** AI/ML Architecture:
** Deep understanding of modern AI/ML architectures including transformer models, retrieval-augmented generation (RAG), agent frameworks, and model orchestration patterns
* ** Analytical Thinking:
** Expert knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems.
* ** Cloud AI Platforms:
** Hands-on experience with major cloud AI platforms (Azure OpenAI Service, AWS Bedrock, Google Vertex AI) and ability to architect multi-cloud or hybrid solutions
* ** Requirements Analysis:
** Expert knowledge of tools, methods, and techniques of requirement analysis; ability to elicit, analyze and record required business functionality and non-functionality requirements to ensure the success of a system or software development project.
* ** Data Architecture:
** Expert knowledge of processes, techniques and factors that affect data architecture; ability to design blueprints on how to integrate data resources for business processes and functional support.
* ** Target Architecture:
** Expert knowledge of target architecture; ability to develop the IT blueprint and roadmap while aligning the architecture and processes with business strategies and objectives.
* ** MLOps:
** Strong knowledge of MLOps practices including model versioning, deployment pipelines, monitoring, and governance frameworks
** Considerations for Top Candidates:
*** Deep experience designing and building agentic AI systems, including multi-agent architectures, tool use and orchestration patterns
* Experience designing and implementing production AI agent systems using frameworks like Lang Chain, Lang Graph, Semantic Kernel, or similar orchestration tools
* Strong understanding of LLM capabilities, limitations and deployment patterns (prompt engineering, RAG, function calling, context engineering)
* Experience evaluating and integrating AI/ML infrastructure components (vector databases, embedding models, orchestration layers, observability tools)
* Broad…